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Do Too Many Cooks Spoil the Broth? Using the Number of Developers to Enhance Defect Prediction Models
AT&T Labs Res, Florham Pk, NJ 07932 USA.ORCID iD: 0000-0002-1660-199X
AT&T Labs Res, Florham Pk, NJ 07932 USA.
AT&T Labs Res, Florham Pk, NJ 07932 USA.
2008 (English)In: Journal of Empirical Software Engineering, ISSN 1382-3256, E-ISSN 1573-7616, Vol. 13, no 5, 539-559 p.Article in journal (Refereed) Published
Abstract [en]

Fault prediction by negative binomial regression models is shown to be effective for four large production software systems from industry. A model developed originally with data from systems with regularly scheduled releases was successfully adapted to a system without releases to identify 20% of that system's files that contained 75% of the faults. A model with a pre-specified set of variables derived from earlier research was applied to three additional systems, and proved capable of identifying averages of 81, 94 and 76% of the faults in those systems. A primary focus of this paper is to investigate the impact on predictive accuracy of using data about the number of developers who access individual code units. For each system, including the cumulative number of developers who had previously modified a file yielded no more than a modest improvement in predictive accuracy. We conclude that while many factors can "spoil the broth" (lead to the release of software with too many defects), the number of developers is not a major influence.

Place, publisher, year, edition, pages
2008. Vol. 13, no 5, 539-559 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mdh:diva-23700DOI: 10.1007/s10664-008-9082-8ISI: 000259369000004Scopus ID: 2-s2.0-52549112910OAI: oai:DiVA.org:mdh-23700DiVA: diva2:680449
Available from: 2013-12-18 Created: 2013-12-18 Last updated: 2014-06-18Bibliographically approved

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